Early Detection of Fire Blight Disease of Pome Fruit Trees Using Visible-NIR Spectrometry and Dimensionality Reduction Methods

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BAGHERI N.; Mohamadi Monavar h.

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Paper Information

Journal: JOURNAL OF AGRICULTURAL MACHINERY Year:2020 | Volume:10 | Issue:1 (19) Page(s): 37-48

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Information Journal Paper

Title

Early Detection of Fire Blight Disease of Pome Fruit Trees Using Visible-NIR Spectrometry and Dimensionality Reduction Methods

Author(s)

BAGHERI N. | Mohamadi Monavar h. | Issue Writer Certificate

Keywords

Early detectionQ1

Fire blightQ1

Precision agricultureQ1

Remote sensingQ1

Vis/NIR SpectrometryQ1

Abstract

Fire blight (FB) is the most destructive bacterial disease of pome fruit trees around the world. In recent years, spectrometry has been shown to be an accurate and real-time sensing technology for plant disease detection. So, the main objective of this research is early detecting FB of pear trees by using Visible-Near-infrared spectrometry. To get this goal, the reflectance spectra of healthy leaves (ND), non-symptomatic (NS), and symptomatic diseased leaves (SY) were captured in the visible– NIR spectral regions. In order to keep the important information of spectra and reduce the dimension of data, three linear and non-linear manifold-based learning techniques were applied such as, Principal Component Analysis (PCA), Sammon mapping and Multilayer auto-encoder (MAE). The output of manifold-based learning techniques was used as an input of the SIMCA (Soft independent modeling by class analogy) classification model to discriminate NS and ND leaves. Based on the results, the best classification accuracy obtained by using PCA on the 1st derivative spectra, with accuracy of 95. 8%, 89. 3%, and 91. 6% for ND, NS, and SY samples, respectively. These results support the capability of manifold-based learning techniques for Early detection of FB via spectrometry method.

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APA: Copy

BAGHERI, N., & Mohamadi Monavar, h.. (2020). Early Detection of Fire Blight Disease of Pome Fruit Trees Using Visible-NIR Spectrometry and Dimensionality Reduction Methods. JOURNAL OF AGRICULTURAL MACHINERY, 10(1 (19) ), 37-48. SID. https://sid.ir/paper/400555/en

Vancouver: Copy

BAGHERI N., Mohamadi Monavar h.. Early Detection of Fire Blight Disease of Pome Fruit Trees Using Visible-NIR Spectrometry and Dimensionality Reduction Methods. JOURNAL OF AGRICULTURAL MACHINERY[Internet]. 2020;10(1 (19) ):37-48. Available from: https://sid.ir/paper/400555/en

IEEE: Copy

N. BAGHERI, and h. Mohamadi Monavar, “Early Detection of Fire Blight Disease of Pome Fruit Trees Using Visible-NIR Spectrometry and Dimensionality Reduction Methods,” JOURNAL OF AGRICULTURAL MACHINERY, vol. 10, no. 1 (19) , pp. 37–48, 2020, [Online]. Available: https://sid.ir/paper/400555/en

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